Blog Archives

Coupling of particle filters: smoothing

July 20, 2016
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Coupling of particle filters: smoothing

    Hi again! In this post, I’ll explain the new smoother introduced in our paper Coupling of Particle Filters with Fredrik Lindsten and Thomas B. Schön from Uppsala University. Smoothing refers to the task of estimating a latent process of length , given noisy measurements of it, ; the smoothing distribution refers to . The setting is state-space […]

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Coupling of particle filters: likelihood curves

July 19, 2016
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Coupling of particle filters: likelihood curves

Hi! In this post, I’ll write about coupling particle filters, as proposed in our recent paper with Fredrik Lindsten and Thomas B. Schön from Uppsala University, available on arXiv; and also in this paper by colleagues at NUS. The paper is about a methodology with multiple direct consequences. In this first post, I’ll focus on correlated likelihood estimators; in a later […]

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Sequential Bayesian inference for time series

May 19, 2015
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Sequential Bayesian inference for time series

Hello hello, I have just arXived a review article, written for ESAIM: Proceedings and Surveys, called Sequential Bayesian inference for implicit hidden Markov models and current limitations. The topic is sequential Bayesian estimation: you want to perform inference (say, parameter inference, or prediction of future observations), taking into account parameter and model uncertainties, using hidden Markov […]

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Sequential Bayesian inference for time series

May 19, 2015
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Sequential Bayesian inference for time series

Hello hello, I have just arXived a review article, written for ESAIM: Proceedings and Surveys, called Sequential Bayesian inference for implicit hidden Markov models and current limitations. The topic is sequential Bayesian estimation: you want to perform inference (say, parameter inference, or prediction of future observations), taking into account parameter and model uncertainties, using hidden Markov […]

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[Meta-]Blogging as young researchers

December 11, 2014
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[Meta-]Blogging as young researchers

Hello all, This is an article intended for the ISBA bulletin, jointly written by us all at Statisfaction, Rasmus Bååth from Publishable Stuff, Boris Hejblum from Research side effects, Thiago G. Martins from tgmstat@wordpress, Ewan Cameron from Another Astrostatistics Blog and Gregory Gandenberger from gandenberger.org.  Inspired by established blogs, such as the popular Statistical Modeling, […]

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Non-negative unbiased estimators

May 13, 2014
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Non-negative unbiased estimators

Hey hey, With Alexandre Thiéry we’ve been working on non-negative unbiased estimators for a while now. Since I’ve been talking about it at conferences and since we’ve just arXived the second version of the article, it’s time for a blog post. This post is kind of a follow-up of a previous post from July, where […]

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Parallel resampling in the particle filter

May 12, 2014
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Parallel resampling in the particle filter

Hey there, It’s been a while I haven’t written about parallelization and GPUs. With colleagues Lawrence Murray and Anthony Lee we have just arXived a new version of Parallel resampling in the particle filter. The setting is that, on modern computing architectures such as GPUs, thousands of operations can be performed in parallel (i.e. simultaneously) […]

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Moustache target distribution and Wes Anderson

March 31, 2014
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Moustache target distribution and Wes Anderson

Today I am going to introduce the moustache target distribution (moustarget distribution for brievety). Load some packages first. Let’s invoke the moustarget distribution. This defines a target distribution represented by a SVG file using RShapeTarget. The target probability density function is defined on and is proportional to on the segments described in the SVG files, […]

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Rasmus Bååth’s Bayesian first aid

January 23, 2014
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Rasmus Bååth’s Bayesian first aid

Besides having coded a pretty cool MCMC app in Javascript, this guy Rasmus Bååth has started the Bayesian first aid project. The idea is that if there’s an R function called blabla.test performing test “blabla”, there should be a function bayes.blabla.test performing a similar test in a Bayesian framework, and showing the output in a […]

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From SVG to probability distributions [with R package]

August 25, 2013
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From SVG to probability distributions [with R package]

Hey, To illustrate generally complex probability density functions on continuous spaces, researchers always use the same examples, for instance mixtures of Gaussian distributions or a banana shaped distribution defined on with density function: If we draw a sample from this distribution using MCMC we obtain a [scatter]plot like this one: Clearly it doesn’t really look […]

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